Robotic devices are increasingly being used in a wide-variety of applications, such as in healthcare, manufacturing, and user-assistive applications. As the use of robots become more widespread, end-users that are not trained in the programming and control of robotic devices may have a need to use such devices. For example, a disabled person may have a need to use a servant robot to retrieve items or help him or her into and out of bed. However, the disabled person may not have been subjected to the extensive robotic programming training required to control the robot to perform desired tasks. Currently, users program the robot with complicated trajectory patterns to teach the robot to perform tasks. Further, manual control of a robot may be very tedious for the user. The user commonly must make all of the necessary judgments in accordance with the particular situation of the target object and/or ambient environment that the robot is located.
Accordingly, a need exists for alternative human-robot interface apparatuses and methods for the control of robots that enable object recognition and limit the need for user intervention.